Internet of Things, Network Functions, Big Data Systems, and Clouds

Distributed Applications, Complex Services, and Middleware

About

Service Engineering Analytics - (SEA) - Team concentrates and consolidates research activities, resources, results, and collaborations on Systems, Software and Data Service Engineering Analytics carried out under the lead of Hong-Linh Truong at Faculty of Informatics, TU Wien.

Service Engineering Analytics

Engineering analytics is concerned with the techniques and tools for desiging, monitoring, analyzing, and optimizing functions, performance, data quality, elasticity, and uncertainties associated with systems, software, data and services.
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In our work, we focus on engineering analytics for: Systems (IoT, Cloud, and Edge Systems), Software (Middleware, Protocols, and Tools) , Data (Processing Models and Analytics), Services (Data Marketplace, Service Models, APIs, and Configuration). We apply our engineering analytics techniques to various applications, including smart cities, smart agriculture, enterprises, e-science, logistics, robotics, and e-health.
Many results of our research are also reflected in our Advanced Services Engineering course for PhD/Master students at TU Wien and the Distributed Systems Technologies course for master studies.

Software

We focus on system software, middleware, tools and applications in the IoT, cloud, edge/fog, cyber-physical systems, and social-cyber-physical systems. Application domains are smart agriculture, smart city, e-science, and industrial internet. Some recent tools are IoT management, Uncertainty Testing for CPS

Data

We focus on data models and data analytics, including various types of data in complex distributed systems that are gathered, processed and provisioned under different services. Some our novel concepts are elastic data analytics

Services

Services offer functions built on capabilities of the above-mentioned systems, software and data. We focus on novel technical service models (data-as-a-service, IoT services, e-science services, and several application-specific services), service API and execution management, and dynamic business models (e.g. pay-per-use) for consumers. Some of our novel conconcepts are Data-as-a-Service, data contracts for data marketplaces, human sensing data marketplace, and IoT data marketplaces